Marketers can easily trade in their old infrastructure for a privacy centric measurement platform which measures true value at an operational level using causal AI.

We are excited to announce the launch of Explorer, a revolutionary new marketing attribution platform using Causal AI.

Legacy marketing measurement methods like last-click attribution relied on user level data. But as this data is no longer available with the deprecation of the IDFA, Cookie, and GAID, marketers are left with faulty attribution reports which are full of inaccuracies. 
In this wake, some marketers turned to media mix modeling (MMM), but discovered that it does not provide the granularity required for tactical operations. Others are fashioning their own incrementality experiments, hiring data science resources to conduct “hold out” studies which force them to make big changes, and still will often lead to a result that is not significant.

INCRMNTAL fills the measurement gap by introducing the first ever incrementality measurement platform based on causal AI. 
Using proprietary developed causal AI models, INCRMNTAL’s newest platform continuously measures each and every marketing tactic, without the need for experiments or A/B testing, to provide always-on measurement of marketing contribution and marginal performance. Its breakthrough approach is receiving attention by academic researchers at several leading universities across the United States and Israel.  

“The platform just became a lot simpler for marketers to use, as it looks just like standard marketing reports, while the underlying technology offers the heavily lifting to provide incrementality and marginal results for any channel” said Maor Sadra, CEO of INCRMNTAL.

This capability is the first of its kind in the industry and enables marketers to understand which channels are meeting their KPIs, and which have reached a point of saturation. By combining the absolute and marginal value, advertisers see exactly where they should be spending their next dollar. As a result, marketers can use INCRMNTAL’s powerful privacy-safe platform to make informed budget decisions that drive the optimum ROI.

Moti Tal, CTO and Co-Founder explains the innovation behind this groundbreaking methodology. “In contrast to conventional A/B testing, randomized controlled trials, or observational studies such as GeoLift experiments, INCRMNTAL’s methodology employs time series interruptions and causal discovery to identify and predict potential outcomes in the absence of any interventions in the data.”

“Through extensive research, the company has constructed an assembled model based on various time series prediction models. These diverse models, each with its own strengths and drawbacks, can interact with external features, encompassing short-term seasonality and long-term effects, and their combined outcomes provides a highly robust solution for time series prediction in face of noisy data affected by a wide range of both observable and unobservable predictions. The models are not calibrated, or customized, as the AI component learns the variables and runs the causal discovery on its own” says Moti.  

To further refine the approach beyond singular measurements, which focus on individual points in time, INCRMNTAL developed a continuous measurement algorithm intended on predicting all dimensions consistently over time. This algorithm establishes a baseline for activities against which all contributions are evaluated. By applying the causal discovery distribution algorithm to the continuous measurement, we can derive the short and long-term interactions of entities over time across all necessary dimensions.

Building upon the continuous system, the company developed a mechanism to calculate the true value for a given time period of every measured KPI, encompassing both marginal KPIs and absolute numerical values. This is achieved through the utilization of a comprehensive  fitted function mechanism, using the continuous mechanism as input, and is contributing to the comprehensive understanding derived from the data.”

About the Product
The new platform, which is already being used by large scale marketing organizations including Hopper, Binance, Self Financial, SEGA, AutoScout24, and Gameloft is available to all customers of INCRMNTAL, promising to:

• Increase efficiency by understanding the true contribution of each advertising channel
• Eliminating the dependency on last-click attribution, or any form of user tracking
• Analyzing the incremental contribution of each channel, platform, and country, without conducting any planned experiment
• Measure performance across all channels including iOS, Android, Web, TV, CTV, Influencer marketing 
• Allow marketers to explore the prediction models rather than just trusting a “black box” 
• Measure the impact of external effects on marketing efforts 
   

Maor Sadra, CEO at INCRMNTAL, said: “When we started INCRMNTAL we had a clear vision - to evolve marketing from counting clicks to measuring value. We wanted to provide advertisers with privacy-safe, accurate measurement across all channels, online and offline, without the need for experiments or user-level data. With this new innovation, I believe that we are achieving this. The feedback from our customers, some of the world’s most sophisticated Advertisers, has been terrific. We are happy to continue being in the forefront of innovation exactly when the market needs it”